Reservoir computing is a recently developed class of machine learning, and can be useful for time domain applications. Reservoir computing techniques can include performing matrix operations, such as linear or nonlinear matrix multiplication. However, when matrix dimensions can be on the order of 1000s by 100000s or more, the matrix operations can take a significant amount of computational time and power.